Loan_dataset

Dataset statistics

Number of variables	41
Number of observations	24301
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	7.6 MiB
Average record size in memory	328.0 B

Variable types

Numeric	21
Categorical	20

Alerts

`int_rate` has a high cardinality: 361 distinct values	High cardinality
`emp_title` has a high cardinality: 19414 distinct values	High cardinality
`issue_d` has a high cardinality: 55 distinct values	High cardinality
`desc` has a high cardinality: 16214 distinct values	High cardinality
`title` has a high cardinality: 12699 distinct values	High cardinality
`zip_code` has a high cardinality: 783 distinct values	High cardinality
`earliest_cr_line` has a high cardinality: 495 distinct values	High cardinality
`revol_util` has a high cardinality: 1059 distinct values	High cardinality
`last_pymnt_d` has a high cardinality: 102 distinct values	High cardinality
`last_credit_pull_d` has a high cardinality: 102 distinct values	High cardinality
`loan_amnt` is highly correlated with `funded_amnt` and 6 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`installment` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`loan_status` is highly correlated with `recoveries` and 1 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`recoveries` is highly correlated with `loan_status` and 1 other fields	High correlation
`collection_recovery_fee` is highly correlated with `loan_status` and 1 other fields	High correlation
`last_pymnt_amnt` is highly correlated with `total_pymnt` and 1 other fields	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`loan_amnt` is highly correlated with `funded_amnt` and 6 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`term` is highly correlated with `total_rec_int`	High correlation
`installment` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`recoveries` is highly correlated with `collection_recovery_fee`	High correlation
`collection_recovery_fee` is highly correlated with `recoveries`	High correlation
`last_pymnt_amnt` is highly correlated with `total_pymnt` and 2 other fields	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`loan_amnt` is highly correlated with `funded_amnt` and 6 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`installment` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`loan_status` is highly correlated with `recoveries` and 1 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`recoveries` is highly correlated with `loan_status` and 1 other fields	High correlation
`collection_recovery_fee` is highly correlated with `loan_status` and 1 other fields	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`sub_grade` is highly correlated with `grade`	High correlation
`grade` is highly correlated with `sub_grade`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`loan_amnt` is highly correlated with `funded_amnt` and 7 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`term` is highly correlated with `sub_grade` and 1 other fields	High correlation
`installment` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`grade` is highly correlated with `sub_grade`	High correlation
`sub_grade` is highly correlated with `term` and 2 other fields	High correlation
`loan_status` is highly correlated with `total_rec_prncp`	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 8 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 8 other fields	High correlation
`recoveries` is highly correlated with `collection_recovery_fee`	High correlation
`collection_recovery_fee` is highly correlated with `recoveries`	High correlation
`last_pymnt_amnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`annual_inc` is highly skewed (γ1 = 36.43261349)	Skewed
`collection_recovery_fee` is highly skewed (γ1 = 22.72682334)	Skewed
`df_index` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`delinq_2yrs` has 21691 (89.3%) zeros	Zeros
`inq_last_6mths` has 11833 (48.7%) zeros	Zeros
`revol_bal` has 606 (2.5%) zeros	Zeros
`total_rec_late_fee` has 23074 (95.0%) zeros	Zeros
`recoveries` has 21677 (89.2%) zeros	Zeros
`collection_recovery_fee` has 21936 (90.3%) zeros	Zeros

Reproduction

Analysis started	2021-10-24 13:23:30.390234
Analysis finished	2021-10-24 13:25:03.606381
Duration	1 minute and 33.22 seconds
Software version	pandas-profiling v3.1.1
Download configuration	config.json

df_index
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	24301
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12505.21843

Minimum	0
Maximum	24998
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	1248
Q1	6241
median	12510
Q3	18761
95-th percentile	23758
Maximum	24998
Range	24998
Interquartile range (IQR)	12520

Descriptive statistics

Standard deviation	7222.96211
Coefficient of variation (CV)	0.5775958375
Kurtosis	-1.200918075
Mean	12505.21843
Median Absolute Deviation (MAD)	6260
Skewness	-0.0008194499169
Sum	303889313
Variance	52171181.65
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2047	1	< 0.1%
23182	1	< 0.1%
10880	1	< 0.1%
8833	1	< 0.1%
14978	1	< 0.1%
12931	1	< 0.1%
2692	1	< 0.1%
645	1	< 0.1%
4743	1	< 0.1%
19084	1	< 0.1%
Other values (24291)	24291	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
24998	1	< 0.1%
24997	1	< 0.1%
24996	1	< 0.1%
24995	1	< 0.1%
24994	1	< 0.1%
24993	1	< 0.1%
24992	1	< 0.1%
24991	1	< 0.1%
24990	1	< 0.1%
24989	1	< 0.1%

loan_amnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	762
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11108.38443

Minimum	500
Maximum	35000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	500
5-th percentile	2400
Q1	5500
median	10000
Q3	15000
95-th percentile	25000
Maximum	35000
Range	34500
Interquartile range (IQR)	9500

Descriptive statistics

Standard deviation	7295.67766
Coefficient of variation (CV)	0.6567721622
Kurtosis	0.8052426437
Mean	11108.38443
Median Absolute Deviation (MAD)	5000
Skewness	1.058928957
Sum	269944850
Variance	53226912.52
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	1787	7.4%
12000	1454	6.0%
5000	1239	5.1%
6000	1211	5.0%
15000	1162	4.8%
20000	988	4.1%
8000	955	3.9%
25000	847	3.5%
4000	678	2.8%
3000	641	2.6%
Other values (752)	13339	54.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
500	2	< 0.1%
900	2	< 0.1%
950	1	< 0.1%
1000	164	0.7%
1050	3	< 0.1%
1100	3	< 0.1%
1125	1	< 0.1%
1150	1	< 0.1%
1200	85	0.3%
1250	6	< 0.1%

Value	Count	Frequency (%)
35000	353	1.5%
34800	2	< 0.1%
34525	1	< 0.1%
34475	4	< 0.1%
34200	1	< 0.1%
34000	11	< 0.1%
33950	5	< 0.1%
33600	3	< 0.1%
33500	1	< 0.1%
33250	1	< 0.1%

funded_amnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	929
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10836.68882

Minimum	500
Maximum	35000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	500
5-th percentile	2400
Q1	5500
median	9600
Q3	15000
95-th percentile	25000
Maximum	35000
Range	34500
Interquartile range (IQR)	9500

Descriptive statistics

Standard deviation	7032.562475
Coefficient of variation (CV)	0.6489586065
Kurtosis	1.006439294
Mean	10836.68882
Median Absolute Deviation (MAD)	4600
Skewness	1.089169338
Sum	263342375
Variance	49456934.97
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	1734	7.1%
12000	1400	5.8%
5000	1233	5.1%
6000	1205	5.0%
15000	1088	4.5%
8000	947	3.9%
20000	868	3.6%
25000	691	2.8%
4000	677	2.8%
3000	637	2.6%
Other values (919)	13821	56.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
500	2	< 0.1%
900	2	< 0.1%
950	1	< 0.1%
1000	164	0.7%
1050	3	< 0.1%
1100	3	< 0.1%
1125	1	< 0.1%
1150	1	< 0.1%
1200	87	0.4%
1250	6	< 0.1%

Value	Count	Frequency (%)
35000	295	1.2%
34800	1	< 0.1%
34525	1	< 0.1%
34475	3	< 0.1%
34250	1	< 0.1%
34000	10	< 0.1%
33950	4	< 0.1%
33600	3	< 0.1%
33500	1	< 0.1%
33250	1	< 0.1%

funded_amnt_inv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5415
Distinct (%)	22.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10275.87399

Minimum	0
Maximum	35000
Zeros	87
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	1963.54
Q1	5000
median	8925
Q3	14025
95-th percentile	24470.7045
Maximum	35000
Range	35000
Interquartile range (IQR)	9025

Descriptive statistics

Standard deviation	6965.327422
Coefficient of variation (CV)	0.6778330901
Kurtosis	1.141229871
Mean	10275.87399
Median Absolute Deviation (MAD)	4125
Skewness	1.11382658
Sum	249714013.9
Variance	48515786.09
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	813	3.3%
5000	791	3.3%
6000	762	3.1%
12000	659	2.7%
8000	526	2.2%
3000	500	2.1%
4000	475	2.0%
15000	394	1.6%
7000	377	1.6%
2000	277	1.1%
Other values (5405)	18727	77.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	87	0.4%
0.000654607	1	< 0.1%
0.001867696	1	< 0.1%
0.001963093	1	< 0.1%
0.002283598	1	< 0.1%
0.002373058	1	< 0.1%
0.002915021	1	< 0.1%
0.003084491	1	< 0.1%
0.00310016	1	< 0.1%
0.00435368	1	< 0.1%

Value	Count	Frequency (%)
35000	75	0.3%
34993.65539	1	< 0.1%
34993.32571	1	< 0.1%
34993.19696	1	< 0.1%
34977.34674	1	< 0.1%
34975.81636	1	< 0.1%
34975	48	0.2%
34972.35245	1	< 0.1%
34972.12183	1	< 0.1%
34972.05982	1	< 0.1%

term
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

36	18203
60	6098

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	48602
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	36
2nd row	36
3rd row	36
4th row	60
5th row	36

Common Values

Value	Count	Frequency (%)
36	18203	74.9%
60	6098	25.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
36	18203	74.9%
60	6098	25.1%

Most occurring characters

Value	Count	Frequency (%)
6	24301	50.0%
3	18203	37.5%
0	6098	12.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	48602	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
6	24301	50.0%
3	18203	37.5%
0	6098	12.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	48602	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
6	24301	50.0%
3	18203	37.5%
0	6098	12.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	48602	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
6	24301	50.0%
3	18203	37.5%
0	6098	12.5%

int_rate
Categorical

HIGH CARDINALITY

Distinct	361
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

10.99%	575
7.51%	496
11.49%	479
7.88%	476
13.49%	470
Other values (356)	21805

Length

Max length	6
Median length	6
Mean length	5.690177359
Min length	5

Characters and Unicode

Total characters	138277
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	28 ?
Unique (%)	0.1%

Sample

1st row	7.51%
2nd row	8.94%
3rd row	13.57%
4th row	17.49%
5th row	8.94%

Common Values

Value	Count	Frequency (%)
10.99%	575	2.4%
7.51%	496	2.0%
11.49%	479	2.0%
7.88%	476	2.0%
13.49%	470	1.9%
7.49%	425	1.7%
9.99%	357	1.5%
5.42%	355	1.5%
7.90%	348	1.4%
11.71%	341	1.4%
Other values (351)	19979	82.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
10.99	575	2.4%
7.51	496	2.0%
11.49	479	2.0%
7.88	476	2.0%
13.49	470	1.9%
7.49	425	1.7%
9.99	357	1.5%
5.42	355	1.5%
7.90	348	1.4%
11.71	341	1.4%
Other values (351)	19979	82.2%

Most occurring characters

Value	Count	Frequency (%)
%	24301	17.6%
.	24301	17.6%
1	23247	16.8%
9	13140	9.5%
2	7772	5.6%
6	7466	5.4%
7	7362	5.3%
4	6818	4.9%
5	6155	4.5%
3	6119	4.4%
Other values (2)	11596	8.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	89675	64.9%
Other Punctuation	48602	35.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	23247	25.9%
9	13140	14.7%
2	7772	8.7%
6	7466	8.3%
7	7362	8.2%
4	6818	7.6%
5	6155	6.9%
3	6119	6.8%
8	5915	6.6%
0	5681	6.3%

Other Punctuation

Value	Count	Frequency (%)
%	24301	50.0%
.	24301	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	138277	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
%	24301	17.6%
.	24301	17.6%
1	23247	16.8%
9	13140	9.5%
2	7772	5.6%
6	7466	5.4%
7	7362	5.3%
4	6818	4.9%
5	6155	4.5%
3	6119	4.4%
Other values (2)	11596	8.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	138277	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
%	24301	17.6%
.	24301	17.6%
1	23247	16.8%
9	13140	9.5%
2	7772	5.6%
6	7466	5.4%
7	7362	5.3%
4	6818	4.9%
5	6155	4.5%
3	6119	4.4%
Other values (2)	11596	8.4%

installment
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	11351
Distinct (%)	46.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	323.714343

Minimum	16.08
Maximum	1305.19
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	16.08
5-th percentile	73.26
Q1	167.78
median	280.97
Q3	426.47
95-th percentile	750.75
Maximum	1305.19
Range	1289.11
Interquartile range (IQR)	258.69

Descriptive statistics

Standard deviation	206.7294246
Coefficient of variation (CV)	0.6386168208
Kurtosis	1.287578775
Mean	323.714343
Median Absolute Deviation (MAD)	121.87
Skewness	1.133111451
Sum	7866582.25
Variance	42737.055
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
311.11	47	0.2%
180.96	35	0.1%
311.02	35	0.1%
186.61	30	0.1%
339.31	30	0.1%
187.69	30	0.1%
312.82	29	0.1%
303.27	28	0.1%
150.8	27	0.1%
373.33	27	0.1%
Other values (11341)	23983	98.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
16.08	1	< 0.1%
16.47	1	< 0.1%
21.25	1	< 0.1%
22.94	1	< 0.1%
23.17	1	< 0.1%
23.51	1	< 0.1%
24.16	1	< 0.1%
24.27	1	< 0.1%
24.32	1	< 0.1%
24.73	1	< 0.1%

Value	Count	Frequency (%)
1305.19	1	< 0.1%
1295.21	1	< 0.1%
1288.1	1	< 0.1%
1283.5	1	< 0.1%
1276.6	2	< 0.1%
1272.2	1	< 0.1%
1269.73	3	< 0.1%
1265.16	1	< 0.1%
1263.23	1	< 0.1%
1257.98	2	< 0.1%

grade
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

B	7290
A	6270
C	4929
D	3295
E	1693
Other values (2)	824

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	24301
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A
2nd row	A
3rd row	C
4th row	D
5th row	A

Common Values

Value	Count	Frequency (%)
B	7290	30.0%
A	6270	25.8%
C	4929	20.3%
D	3295	13.6%
E	1693	7.0%
F	626	2.6%
G	198	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
b	7290	30.0%
a	6270	25.8%
c	4929	20.3%
d	3295	13.6%
e	1693	7.0%
f	626	2.6%
g	198	0.8%

Most occurring characters

Value	Count	Frequency (%)
B	7290	30.0%
A	6270	25.8%
C	4929	20.3%
D	3295	13.6%
E	1693	7.0%
F	626	2.6%
G	198	0.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	24301	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
B	7290	30.0%
A	6270	25.8%
C	4929	20.3%
D	3295	13.6%
E	1693	7.0%
F	626	2.6%
G	198	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	24301	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
B	7290	30.0%
A	6270	25.8%
C	4929	20.3%
D	3295	13.6%
E	1693	7.0%
F	626	2.6%
G	198	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24301	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
B	7290	30.0%
A	6270	25.8%
C	4929	20.3%
D	3295	13.6%
E	1693	7.0%
F	626	2.6%
G	198	0.8%

sub_grade
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	35
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

A4	1824
A5	1741
B3	1716
B5	1677
B4	1532
Other values (30)	15811

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	48602
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A4
2nd row	A5
3rd row	C3
4th row	D5
5th row	A5

Common Values

Value	Count	Frequency (%)
A4	1824	7.5%
A5	1741	7.2%
B3	1716	7.1%
B5	1677	6.9%
B4	1532	6.3%
C1	1290	5.3%
B2	1259	5.2%
C2	1217	5.0%
A3	1107	4.6%
B1	1106	4.6%
Other values (25)	9832	40.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
a4	1824	7.5%
a5	1741	7.2%
b3	1716	7.1%
b5	1677	6.9%
b4	1532	6.3%
c1	1290	5.3%
b2	1259	5.2%
c2	1217	5.0%
a3	1107	4.6%
b1	1106	4.6%
Other values (25)	9832	40.5%

Most occurring characters

Value	Count	Frequency (%)
B	7290	15.0%
A	6270	12.9%
4	5099	10.5%
5	5036	10.4%
3	4939	10.2%
C	4929	10.1%
2	4818	9.9%
1	4409	9.1%
D	3295	6.8%
E	1693	3.5%
Other values (2)	824	1.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	24301	50.0%
Decimal Number	24301	50.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
B	7290	30.0%
A	6270	25.8%
C	4929	20.3%
D	3295	13.6%
E	1693	7.0%
F	626	2.6%
G	198	0.8%

Decimal Number

Value	Count	Frequency (%)
4	5099	21.0%
5	5036	20.7%
3	4939	20.3%
2	4818	19.8%
1	4409	18.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	24301	50.0%
Common	24301	50.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
B	7290	30.0%
A	6270	25.8%
C	4929	20.3%
D	3295	13.6%
E	1693	7.0%
F	626	2.6%
G	198	0.8%

Common

Value	Count	Frequency (%)
4	5099	21.0%
5	5036	20.7%
3	4939	20.3%
2	4818	19.8%
1	4409	18.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	48602	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
B	7290	15.0%
A	6270	12.9%
4	5099	10.5%
5	5036	10.4%
3	4939	10.2%
C	4929	10.1%
2	4818	9.9%
1	4409	9.1%
D	3295	6.8%
E	1693	3.5%
Other values (2)	824	1.7%

emp_title
Categorical

HIGH CARDINALITY

Distinct	19414
Distinct (%)	79.9%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

Bank of America	107
IBM	65
AT&T	57
Kaiser Permanente	56
Lockheed Martin	42
Other values (19409)	23974

Length

Max length	78
Median length	18
Mean length	18.47672935
Min length	0

Characters and Unicode

Total characters	449003
Distinct characters	92
Distinct categories	14 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17319 ?
Unique (%)	71.3%

Sample

1st row	15
2nd row	1400
3rd row	36000
4th row	old palm inc
5th row	Brocade Communications

Common Values

Value	Count	Frequency (%)
Bank of America	107	0.4%
IBM	65	0.3%
AT&T	57	0.2%
Kaiser Permanente	56	0.2%
Lockheed Martin	42	0.2%
JPMorgan Chase	35	0.1%
JP Morgan Chase	35	0.1%
Department of Defense	35	0.1%
Booz Allen Hamilton	34	0.1%
Northrop Grumman	34	0.1%
Other values (19404)	23801	97.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
inc	2207	3.4%
of	1891	2.9%
	851	1.3%
and	677	1.0%
city	589	0.9%
county	588	0.9%
services	550	0.8%
bank	543	0.8%
center	534	0.8%
school	475	0.7%
Other values (14017)	56550	86.4%

Most occurring characters

Value	Count	Frequency (%)
	42144	9.4%
e	36072	8.0%
a	29265	6.5%
n	29008	6.5%
o	28301	6.3%
i	26371	5.9%
r	26066	5.8%
t	24720	5.5%
s	19451	4.3%
l	17413	3.9%
Other values (82)	170192	37.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	321540	71.6%
Uppercase Letter	77978	17.4%
Space Separator	42144	9.4%
Other Punctuation	5770	1.3%
Decimal Number	732	0.2%
Dash Punctuation	630	0.1%
Open Punctuation	94	< 0.1%
Close Punctuation	93	< 0.1%
Math Symbol	14	< 0.1%
Other Symbol	2	< 0.1%
Other values (4)	6	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
C	10745	13.8%
A	6371	8.2%
S	5874	7.5%
I	5416	6.9%
M	4936	6.3%
L	4144	5.3%
P	4085	5.2%
B	3858	4.9%
E	3831	4.9%
D	3796	4.9%
Other values (18)	24922	32.0%

Lowercase Letter

Value	Count	Frequency (%)
e	36072	11.2%
a	29265	9.1%
n	29008	9.0%
o	28301	8.8%
i	26371	8.2%
r	26066	8.1%
t	24720	7.7%
s	19451	6.0%
l	17413	5.4%
c	15709	4.9%
Other values (17)	69164	21.5%

Other Punctuation

Value	Count	Frequency (%)
.	2594	45.0%
,	1504	26.1%
&	965	16.7%
'	442	7.7%
/	205	3.6%
#	25	0.4%
@	7	0.1%
"	7	0.1%
!	5	0.1%
:	5	0.1%
Other values (4)	11	0.2%

Decimal Number

Value	Count	Frequency (%)
1	152	20.8%
2	128	17.5%
3	115	15.7%
0	73	10.0%
4	70	9.6%
5	53	7.2%
6	44	6.0%
9	43	5.9%
7	31	4.2%
8	23	3.1%

Open Punctuation

Value	Count	Frequency (%)
(	93	98.9%
[	1	1.1%

Math Symbol

Value	Count	Frequency (%)
+	13	92.9%
\|	1	7.1%

Currency Symbol

Value	Count	Frequency (%)
¢	1	50.0%
$	1	50.0%

Space Separator

Value	Count	Frequency (%)
	42144	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	630	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	93	100.0%

Other Symbol

Value	Count	Frequency (%)
©	2	100.0%

Other Number

Value	Count	Frequency (%)
²	2	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	1	100.0%

Control

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	399518	89.0%
Common	49485	11.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	36072	9.0%
a	29265	7.3%
n	29008	7.3%
o	28301	7.1%
i	26371	6.6%
r	26066	6.5%
t	24720	6.2%
s	19451	4.9%
l	17413	4.4%
c	15709	3.9%
Other values (45)	147142	36.8%

Common

Value	Count	Frequency (%)
	42144	85.2%
.	2594	5.2%
,	1504	3.0%
&	965	2.0%
-	630	1.3%
'	442	0.9%
/	205	0.4%
1	152	0.3%
2	128	0.3%
3	115	0.2%
Other values (27)	606	1.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	448993	> 99.9%
None	10	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	42144	9.4%
e	36072	8.0%
a	29265	6.5%
n	29008	6.5%
o	28301	6.3%
i	26371	5.9%
r	26066	5.8%
t	24720	5.5%
s	19451	4.3%
l	17413	3.9%
Other values (75)	170182	37.9%

None

Value	Count	Frequency (%)
Ã	2	20.0%
©	2	20.0%
²	2	20.0%
Â	1	10.0%
â	1	10.0%
	1	10.0%
¢	1	10.0%

emp_length
Real number (ℝ_≥0)

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.021192544

Minimum	0
Maximum	10
Zeros	40
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	4
Q3	9
95-th percentile	10
Maximum	10
Range	10
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	3.381479975
Coefficient of variation (CV)	0.673441607
Kurtosis	-1.37860354
Mean	5.021192544
Median Absolute Deviation (MAD)	3
Skewness	0.3377068344
Sum	122020
Variance	11.43440682
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
10	5315	21.9%
1	4897	20.2%
2	2806	11.5%
3	2675	11.0%
4	2223	9.1%
5	2087	8.6%
6	1385	5.7%
7	1108	4.6%
8	942	3.9%
9	823	3.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	40	0.2%
1	4897	20.2%
2	2806	11.5%
3	2675	11.0%
4	2223	9.1%
5	2087	8.6%
6	1385	5.7%
7	1108	4.6%
8	942	3.9%
9	823	3.4%

Value	Count	Frequency (%)
10	5315	21.9%
9	823	3.4%
8	942	3.9%
7	1108	4.6%
6	1385	5.7%
5	2087	8.6%
4	2223	9.1%
3	2675	11.0%
2	2806	11.5%
1	4897	20.2%

home_ownership
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

RENT	11777
MORTGAGE	10726
OWN	1736
OTHER	62

Length

Max length	8
Median length	4
Mean length	5.696637998
Min length	3

Characters and Unicode

Total characters	138434
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	RENT
2nd row	RENT
3rd row	OWN
4th row	MORTGAGE
5th row	MORTGAGE

Common Values

Value	Count	Frequency (%)
RENT	11777	48.5%
MORTGAGE	10726	44.1%
OWN	1736	7.1%
OTHER	62	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
rent	11777	48.5%
mortgage	10726	44.1%
own	1736	7.1%
other	62	0.3%

Most occurring characters

Value	Count	Frequency (%)
T	22565	16.3%
E	22565	16.3%
R	22565	16.3%
G	21452	15.5%
N	13513	9.8%
O	12524	9.0%
A	10726	7.7%
M	10726	7.7%
W	1736	1.3%
H	62	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	138434	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
T	22565	16.3%
E	22565	16.3%
R	22565	16.3%
G	21452	15.5%
N	13513	9.8%
O	12524	9.0%
A	10726	7.7%
M	10726	7.7%
W	1736	1.3%
H	62	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	138434	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
T	22565	16.3%
E	22565	16.3%
R	22565	16.3%
G	21452	15.5%
N	13513	9.8%
O	12524	9.0%
A	10726	7.7%
M	10726	7.7%
W	1736	1.3%
H	62	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	138434	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
T	22565	16.3%
E	22565	16.3%
R	22565	16.3%
G	21452	15.5%
N	13513	9.8%
O	12524	9.0%
A	10726	7.7%
M	10726	7.7%
W	1736	1.3%
H	62	< 0.1%

annual_inc
Real number (ℝ_≥0)

SKEWED

Distinct	3557
Distinct (%)	14.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	69802.25015

Minimum	4080
Maximum	6000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	4080
5-th percentile	24947.3
Q1	42000
median	60000
Q3	84000
95-th percentile	140900
Maximum	6000000
Range	5995920
Interquartile range (IQR)	42000

Descriptive statistics

Standard deviation	69999.15248
Coefficient of variation (CV)	1.002820859
Kurtosis	2575.276323
Mean	69802.25015
Median Absolute Deviation (MAD)	20000
Skewness	36.43261349
Sum	1696264481
Variance	4899881348
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60000	902	3.7%
50000	662	2.7%
45000	546	2.2%
40000	528	2.2%
75000	504	2.1%
65000	501	2.1%
30000	484	2.0%
70000	470	1.9%
48000	437	1.8%
80000	421	1.7%
Other values (3547)	18846	77.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4080	1	< 0.1%
4200	1	< 0.1%
4800	1	< 0.1%
5500	1	< 0.1%
6000	3	< 0.1%
7200	2	< 0.1%
8000	3	< 0.1%
8004	1	< 0.1%
8472	1	< 0.1%
9600	15	0.1%

Value	Count	Frequency (%)
6000000	1	< 0.1%
3900000	1	< 0.1%
2039784	1	< 0.1%
1900000	1	< 0.1%
1782000	1	< 0.1%
1440000	1	< 0.1%
1362000	1	< 0.1%
1200000	2	< 0.1%
1176000	1	< 0.1%
948000	1	< 0.1%

verification_status
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

Not Verified	10614
Verified	7525
Source Verified	6162

Length

Max length	15
Median length	12
Mean length	11.52207728
Min length	8

Characters and Unicode

Total characters	279998
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Source Verified
2nd row	Not Verified
3rd row	Not Verified
4th row	Not Verified
5th row	Not Verified

Common Values

Value	Count	Frequency (%)
Not Verified	10614	43.7%
Verified	7525	31.0%
Source Verified	6162	25.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
verified	24301	59.2%
not	10614	25.8%
source	6162	15.0%

Most occurring characters

Value	Count	Frequency (%)
e	54764	19.6%
i	48602	17.4%
r	30463	10.9%
d	24301	8.7%
f	24301	8.7%
V	24301	8.7%
	16776	6.0%
o	16776	6.0%
t	10614	3.8%
N	10614	3.8%
Other values (3)	18486	6.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	222145	79.3%
Uppercase Letter	41077	14.7%
Space Separator	16776	6.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	54764	24.7%
i	48602	21.9%
r	30463	13.7%
d	24301	10.9%
f	24301	10.9%
o	16776	7.6%
t	10614	4.8%
c	6162	2.8%
u	6162	2.8%

Uppercase Letter

Value	Count	Frequency (%)
V	24301	59.2%
N	10614	25.8%
S	6162	15.0%

Space Separator

Value	Count	Frequency (%)
	16776	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	263222	94.0%
Common	16776	6.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	54764	20.8%
i	48602	18.5%
r	30463	11.6%
d	24301	9.2%
f	24301	9.2%
V	24301	9.2%
o	16776	6.4%
t	10614	4.0%
N	10614	4.0%
c	6162	2.3%
Other values (2)	12324	4.7%

Common

Value	Count	Frequency (%)
	16776	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	279998	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	54764	19.6%
i	48602	17.4%
r	30463	10.9%
d	24301	8.7%
f	24301	8.7%
V	24301	8.7%
	16776	6.0%
o	16776	6.0%
t	10614	3.8%
N	10614	3.8%
Other values (3)	18486	6.6%

issue_d
Categorical

HIGH CARDINALITY

Distinct	55
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

11-Dec	1280
11-Nov	1258
11-Sep	1234
11-Oct	1184
11-Aug	1141
Other values (50)	18204

Length

Max length	6
Median length	6
Mean length	5.831323814
Min length	5

Characters and Unicode

Total characters	141707
Distinct characters	28
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	10-Sep
2nd row	10-Jan
3rd row	9-Oct
4th row	11-Jul
5th row	9-Dec

Common Values

Value	Count	Frequency (%)
11-Dec	1280	5.3%
11-Nov	1258	5.2%
11-Sep	1234	5.1%
11-Oct	1184	4.9%
11-Aug	1141	4.7%
11-Jul	1098	4.5%
11-Jun	1089	4.5%
11-Apr	1005	4.1%
11-May	1003	4.1%
11-Mar	931	3.8%
Other values (45)	13078	53.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
11-dec	1280	5.3%
11-nov	1258	5.2%
11-sep	1234	5.1%
11-oct	1184	4.9%
11-aug	1141	4.7%
11-jul	1098	4.5%
11-jun	1089	4.5%
11-apr	1005	4.1%
11-may	1003	4.1%
11-mar	931	3.8%
Other values (45)	13078	53.8%

Most occurring characters

Value	Count	Frequency (%)
1	33112	23.4%
-	24301	17.1%
0	7292	5.1%
u	6314	4.5%
e	6313	4.5%
J	5636	4.0%
a	5063	3.6%
c	4957	3.5%
p	4015	2.8%
A	3963	2.8%
Other values (18)	40741	28.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	48602	34.3%
Decimal Number	44503	31.4%
Dash Punctuation	24301	17.1%
Uppercase Letter	24301	17.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	6314	13.0%
e	6313	13.0%
a	5063	10.4%
c	4957	10.2%
p	4015	8.3%
r	3528	7.3%
n	3509	7.2%
v	2495	5.1%
o	2495	5.1%
t	2330	4.8%
Other values (4)	7583	15.6%

Uppercase Letter

Value	Count	Frequency (%)
J	5636	23.2%
A	3963	16.3%
M	3564	14.7%
D	2627	10.8%
N	2495	10.3%
O	2330	9.6%
S	2229	9.2%
F	1457	6.0%

Decimal Number

Value	Count	Frequency (%)
1	33112	74.4%
0	7292	16.4%
9	2996	6.7%
8	953	2.1%
7	150	0.3%

Dash Punctuation

Value	Count	Frequency (%)
-	24301	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	72903	51.4%
Common	68804	48.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
u	6314	8.7%
e	6313	8.7%
J	5636	7.7%
a	5063	6.9%
c	4957	6.8%
p	4015	5.5%
A	3963	5.4%
M	3564	4.9%
r	3528	4.8%
n	3509	4.8%
Other values (12)	26041	35.7%

Common

Value	Count	Frequency (%)
1	33112	48.1%
-	24301	35.3%
0	7292	10.6%
9	2996	4.4%
8	953	1.4%
7	150	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	141707	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	33112	23.4%
-	24301	17.1%
0	7292	5.1%
u	6314	4.5%
e	6313	4.5%
J	5636	4.0%
a	5063	3.6%
c	4957	3.5%
p	4015	2.8%
A	3963	2.8%
Other values (18)	40741	28.8%

loan_status
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

1	20827
0	3474

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	24301
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	20827	85.7%
0	3474	14.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	20827	85.7%
0	3474	14.3%

Most occurring characters

Value	Count	Frequency (%)
1	20827	85.7%
0	3474	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	24301	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	20827	85.7%
0	3474	14.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	24301	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	20827	85.7%
0	3474	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24301	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	20827	85.7%
0	3474	14.3%

desc
Categorical

HIGH CARDINALITY

Distinct	16214
Distinct (%)	66.7%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

	7943
	135
Debt Consolidation	4
debt consolidation	2
Camping Membership	2
Other values (16209)	16215

Length

Max length	3976
Median length	143
Mean length	288.8925559
Min length	0

Characters and Unicode

Total characters	7020378
Distinct characters	139
Distinct categories	17 ?
Distinct scripts	2 ?
Distinct blocks	4 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	16203 ?
Unique (%)	66.7%

Sample

1st row	Borrower added on 08/30/10 > thank you<br/>
2nd row	Borrower added on 01/14/10 > Green city housing project<br/> Borrower added on 01/23/10 > I mistyped in the application. $1400 is the current rent we pay. <br/><br/>My employer is Emerson, and my role is marketing and biz dev director. Been with them for 3 years now. My 2009 annual compensation was ~160K. <br/><br/>I have zero credit card debt or car loans. Purpose of the loan is to buy real estate in my home town in India. It costs ~$140K. Rather than taking a mortgage there, I want to buy the property outright. I used $125K from my savings, and I am short $15K. The name of the building community is Green City - www.vplprojects.com.<br/>
3rd row
4th row	Borrower added on 06/29/11 > thanks for the help.<br/>
5th row

Common Values

Value	Count	Frequency (%)
	7943	32.7%
	135	0.6%
Debt Consolidation	4	< 0.1%
debt consolidation	2	< 0.1%
Camping Membership	2	< 0.1%
refinancing	2	< 0.1%
Borrower added on 09/21/11 > Debt consolidation<br/>	2	< 0.1%
credit card debt consolidation	2	< 0.1%
Motorcycle Loan	2	< 0.1%
I have 2nd mortgage on a rental property with balance of $109k. I have cash flow of $85k and plan to pay off the 2nd mortgage using this loan to make up for rest of the balance. You will see a 2nd mortgage debt on my credit around $965.00 which will go away once this loan is approved as I will be paying it off. The interest rate needs to be below 9% since I can use my credit card to borrow same money for 10%.	2	< 0.1%
Other values (16204)	16205	66.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
i	48123	3.8%
to	44000	3.5%
a	33899	2.7%
the	33491	2.7%
and	33449	2.6%
my	31874	2.5%
on	29722	2.4%
	22434	1.8%
for	20249	1.6%
have	20079	1.6%
Other values (38785)	945839	74.9%

Most occurring characters

Value	Count	Frequency (%)
	1304898	18.6%
e	586334	8.4%
a	440234	6.3%
o	435950	6.2%
t	401109	5.7%
n	376628	5.4%
r	360963	5.1%
i	305383	4.3%
s	261770	3.7%
d	244500	3.5%
Other values (129)	2302609	32.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5008568	71.3%
Space Separator	1304939	18.6%
Decimal Number	210987	3.0%
Other Punctuation	199437	2.8%
Uppercase Letter	182166	2.6%
Math Symbol	85239	1.2%
Currency Symbol	10266	0.1%
Dash Punctuation	8299	0.1%
Close Punctuation	4580	0.1%
Open Punctuation	4182	0.1%
Other values (7)	1715	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	58410	32.1%
B	20955	11.5%
T	17199	9.4%
A	9232	5.1%
M	8661	4.8%
C	8605	4.7%
S	5533	3.0%
W	5308	2.9%
L	5254	2.9%
E	5253	2.9%
Other values (21)	37756	20.7%

Lowercase Letter

Value	Count	Frequency (%)
e	586334	11.7%
a	440234	8.8%
o	435950	8.7%
t	401109	8.0%
n	376628	7.5%
r	360963	7.2%
i	305383	6.1%
s	261770	5.2%
d	244500	4.9%
l	219169	4.4%
Other values (17)	1376528	27.5%

Other Punctuation

Value	Count	Frequency (%)
.	73931	37.1%
/	70589	35.4%
,	30508	15.3%
'	8217	4.1%
!	4228	2.1%
%	3477	1.7%
:	3306	1.7%
;	2056	1.0%
&	1605	0.8%
"	504	0.3%
Other values (10)	1016	0.5%

Control

Value	Count	Frequency (%)
	770	54.3%
	321	22.6%
	147	10.4%
	31	2.2%
	29	2.0%
	25	1.8%
	25	1.8%
	21	1.5%
	18	1.3%
	13	0.9%
Other values (7)	19	1.3%

Decimal Number

Value	Count	Frequency (%)
0	63678	30.2%
1	58777	27.9%
2	22312	10.6%
5	13234	6.3%
3	11014	5.2%
9	10049	4.8%
4	8272	3.9%
6	7927	3.8%
7	7866	3.7%
8	7858	3.7%

Math Symbol

Value	Count	Frequency (%)
>	51369	60.3%
<	32674	38.3%
+	624	0.7%
=	350	0.4%
~	192	0.2%
¬	25	< 0.1%
\|	5	< 0.1%

Other Symbol

Value	Count	Frequency (%)
¦	95	88.8%
©	9	8.4%
®	2	1.9%
�	1	0.9%

Dash Punctuation

Value	Count	Frequency (%)
-	8286	99.8%
—	9	0.1%
–	4	< 0.1%

Close Punctuation

Value	Count	Frequency (%)
)	4559	99.5%
]	18	0.4%
}	3	0.1%

Open Punctuation

Value	Count	Frequency (%)
(	4163	99.5%
[	17	0.4%
{	2	< 0.1%

Modifier Symbol

Value	Count	Frequency (%)
`	8	66.7%
^	3	25.0%
¯	1	8.3%

Space Separator

Value	Count	Frequency (%)
	1304898	> 99.9%
	41	< 0.1%

Currency Symbol

Value	Count	Frequency (%)
$	10220	99.6%
¢	46	0.4%

Final Punctuation

Value	Count	Frequency (%)
’	53	84.1%
”	10	15.9%

Initial Punctuation

Value	Count	Frequency (%)
“	10	90.9%
‘	1	9.1%

Other Number

Value	Count	Frequency (%)
½	5	71.4%
¾	2	28.6%

Connector Punctuation

Value	Count	Frequency (%)
_	96	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5190734	73.9%
Common	1829644	26.1%

Most frequent character per script

Common

Value	Count	Frequency (%)
	1304898	71.3%
.	73931	4.0%
/	70589	3.9%
0	63678	3.5%
1	58777	3.2%
>	51369	2.8%
<	32674	1.8%
,	30508	1.7%
2	22312	1.2%
5	13234	0.7%
Other values (71)	107674	5.9%

Latin

Value	Count	Frequency (%)
e	586334	11.3%
a	440234	8.5%
o	435950	8.4%
t	401109	7.7%
n	376628	7.3%
r	360963	7.0%
i	305383	5.9%
s	261770	5.0%
d	244500	4.7%
l	219169	4.2%
Other values (48)	1558694	30.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7018860	> 99.9%
None	1414	< 0.1%
Punctuation	103	< 0.1%
Specials	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1304898	18.6%
e	586334	8.4%
a	440234	6.3%
o	435950	6.2%
t	401109	5.7%
n	376628	5.4%
r	360963	5.1%
i	305383	4.4%
s	261770	3.7%
d	244500	3.5%
Other values (86)	2301091	32.8%

None

Value	Count	Frequency (%)
â	342	24.2%
	321	22.7%
	147	10.4%
¦	95	6.7%
Â	87	6.2%
Ã	81	5.7%
¢	46	3.3%
	41	2.9%
	31	2.2%
	29	2.1%
Other values (24)	194	13.7%

Punctuation

Value	Count	Frequency (%)
’	53	51.5%
”	10	9.7%
“	10	9.7%
—	9	8.7%
•	8	7.8%
…	8	7.8%
–	4	3.9%
‘	1	1.0%

Specials

Value	Count	Frequency (%)
�	1	100.0%

purpose
Categorical

Distinct	14
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

debt_consolidation	11572
credit_card	3178
other	2397
home_improvement	1826
major_purchase	1348
Other values (9)	3980

Length

Max length	18
Median length	16
Mean length	13.77350726
Min length	3

Characters and Unicode

Total characters	334710
Distinct characters	22
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	home_improvement
2nd row	other
3rd row	major_purchase
4th row	debt_consolidation
5th row	other

Common Values

Value	Count	Frequency (%)
debt_consolidation	11572	47.6%
credit_card	3178	13.1%
other	2397	9.9%
home_improvement	1826	7.5%
major_purchase	1348	5.5%
car	957	3.9%
small_business	930	3.8%
wedding	600	2.5%
medical	429	1.8%
moving	344	1.4%
Other values (4)	720	3.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
debt_consolidation	11572	47.6%
credit_card	3178	13.1%
other	2397	9.9%
home_improvement	1826	7.5%
major_purchase	1348	5.5%
car	957	3.9%
small_business	930	3.8%
wedding	600	2.5%
medical	429	1.8%
moving	344	1.4%
Other values (4)	720	3.0%

Most occurring characters

Value	Count	Frequency (%)
o	43117	12.9%
d	31340	9.4%
t	30989	9.3%
i	30895	9.2%
n	27408	8.2%
e	26659	8.0%
c	21106	6.3%
a	20710	6.2%
_	18914	5.7%
s	16856	5.0%
Other values (12)	66716	19.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	315796	94.3%
Connector Punctuation	18914	5.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	43117	13.7%
d	31340	9.9%
t	30989	9.8%
i	30895	9.8%
n	27408	8.7%
e	26659	8.4%
c	21106	6.7%
a	20710	6.6%
s	16856	5.3%
r	14352	4.5%
Other values (11)	52364	16.6%

Connector Punctuation

Value	Count	Frequency (%)
_	18914	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	315796	94.3%
Common	18914	5.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	43117	13.7%
d	31340	9.9%
t	30989	9.8%
i	30895	9.8%
n	27408	8.7%
e	26659	8.4%
c	21106	6.7%
a	20710	6.6%
s	16856	5.3%
r	14352	4.5%
Other values (11)	52364	16.6%

Common

Value	Count	Frequency (%)
_	18914	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	334710	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	43117	12.9%
d	31340	9.4%
t	30989	9.3%
i	30895	9.2%
n	27408	8.2%
e	26659	8.0%
c	21106	6.3%
a	20710	6.2%
_	18914	5.7%
s	16856	5.0%
Other values (12)	66716	19.9%

title
Categorical

HIGH CARDINALITY

Distinct	12699
Distinct (%)	52.3%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

Debt Consolidation	1351
Debt Consolidation Loan	1022
Personal Loan	429
Consolidation	325
debt consolidation	295
Other values (12694)	20879

Length

Max length	80
Median length	16
Mean length	17.29015267
Min length	0

Characters and Unicode

Total characters	420168
Distinct characters	100
Distinct categories	15 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11432 ?
Unique (%)	47.0%

Sample

1st row	homeimproement
2nd row	Green City
3rd row	payoff w/in 2 years
4th row	save %
5th row	Invest in Lending Club Notes

Common Values

Value	Count	Frequency (%)
Debt Consolidation	1351	5.6%
Debt Consolidation Loan	1022	4.2%
Personal Loan	429	1.8%
Consolidation	325	1.3%
debt consolidation	295	1.2%
Home Improvement	225	0.9%
Debt consolidation	219	0.9%
Credit Card Consolidation	219	0.9%
Personal	188	0.8%
Credit Card Loan	185	0.8%
Other values (12689)	19843	81.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
loan	6654	10.3%
debt	5702	8.9%
consolidation	5326	8.3%
credit	2893	4.5%
card	2095	3.3%
personal	1315	2.0%
home	1156	1.8%
pay	848	1.3%
off	798	1.2%
my	721	1.1%
Other values (6390)	36833	57.2%

Most occurring characters

Value	Count	Frequency (%)
	40788	9.7%
o	40574	9.7%
n	34317	8.2%
e	33449	8.0%
a	31034	7.4%
i	27068	6.4%
t	26268	6.3%
d	19098	4.5%
r	17960	4.3%
s	17318	4.1%
Other values (90)	132294	31.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	320978	76.4%
Uppercase Letter	50832	12.1%
Space Separator	40788	9.7%
Decimal Number	3873	0.9%
Other Punctuation	2817	0.7%
Dash Punctuation	504	0.1%
Connector Punctuation	123	< 0.1%
Close Punctuation	66	< 0.1%
Currency Symbol	64	< 0.1%
Math Symbol	58	< 0.1%
Other values (5)	65	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	40574	12.6%
n	34317	10.7%
e	33449	10.4%
a	31034	9.7%
i	27068	8.4%
t	26268	8.2%
d	19098	5.9%
r	17960	5.6%
s	17318	5.4%
l	16104	5.0%
Other values (17)	57788	18.0%

Uppercase Letter

Value	Count	Frequency (%)
C	11472	22.6%
L	6291	12.4%
D	5679	11.2%
P	3503	6.9%
R	2347	4.6%
M	1921	3.8%
S	1859	3.7%
B	1827	3.6%
E	1760	3.5%
H	1742	3.4%
Other values (17)	12431	24.5%

Other Punctuation

Value	Count	Frequency (%)
!	700	24.8%
'	637	22.6%
.	448	15.9%
/	351	12.5%
,	273	9.7%
&	202	7.2%
%	56	2.0%
:	38	1.3%
"	35	1.2%
*	22	0.8%
Other values (5)	55	2.0%

Decimal Number

Value	Count	Frequency (%)
1	1101	28.4%
0	1092	28.2%
2	696	18.0%
3	197	5.1%
5	169	4.4%
9	164	4.2%
4	150	3.9%
6	111	2.9%
8	104	2.7%
7	89	2.3%

Math Symbol

Value	Count	Frequency (%)
+	30	51.7%
=	12	20.7%
<	9	15.5%
>	6	10.3%
~	1	1.7%

Control

Value	Count	Frequency (%)
	4	44.4%
	2	22.2%
	2	22.2%
	1	11.1%

Close Punctuation

Value	Count	Frequency (%)
)	64	97.0%
]	2	3.0%

Open Punctuation

Value	Count	Frequency (%)
(	49	96.1%
[	2	3.9%

Modifier Symbol

Value	Count	Frequency (%)
`	1	50.0%
^	1	50.0%

Space Separator

Value	Count	Frequency (%)
	40788	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	504	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	123	100.0%

Currency Symbol

Value	Count	Frequency (%)
$	64	100.0%

Other Symbol

Value	Count	Frequency (%)
¦	2	100.0%

Other Number

Value	Count	Frequency (%)
³	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	371810	88.5%
Common	48358	11.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	40574	10.9%
n	34317	9.2%
e	33449	9.0%
a	31034	8.3%
i	27068	7.3%
t	26268	7.1%
d	19098	5.1%
r	17960	4.8%
s	17318	4.7%
l	16104	4.3%
Other values (44)	108620	29.2%

Common

Value	Count	Frequency (%)
	40788	84.3%
1	1101	2.3%
0	1092	2.3%
!	700	1.4%
2	696	1.4%
'	637	1.3%
-	504	1.0%
.	448	0.9%
/	351	0.7%
,	273	0.6%
Other values (36)	1768	3.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	420153	> 99.9%
None	15	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	40788	9.7%
o	40574	9.7%
n	34317	8.2%
e	33449	8.0%
a	31034	7.4%
i	27068	6.4%
t	26268	6.3%
d	19098	4.5%
r	17960	4.3%
s	17318	4.1%
Other values (83)	132279	31.5%

None

Value	Count	Frequency (%)
	4	26.7%
â	4	26.7%
¦	2	13.3%
	2	13.3%
	1	6.7%
Ã	1	6.7%
³	1	6.7%

zip_code
Categorical

HIGH CARDINALITY

Distinct	783
Distinct (%)	3.2%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

100xx	399
112xx	371
945xx	344
606xx	339
070xx	302
Other values (778)	22546

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	121505
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	62 ?
Unique (%)	0.3%

Sample

1st row	076xx
2nd row	300xx
3rd row	310xx
4th row	334xx
5th row	939xx

Common Values

Value	Count	Frequency (%)
100xx	399	1.6%
112xx	371	1.5%
945xx	344	1.4%
606xx	339	1.4%
070xx	302	1.2%
900xx	291	1.2%
021xx	253	1.0%
750xx	247	1.0%
300xx	246	1.0%
331xx	243	1.0%
Other values (773)	21266	87.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
100xx	399	1.6%
112xx	371	1.5%
945xx	344	1.4%
606xx	339	1.4%
070xx	302	1.2%
900xx	291	1.2%
021xx	253	1.0%
750xx	247	1.0%
300xx	246	1.0%
331xx	243	1.0%
Other values (773)	21266	87.5%

Most occurring characters

Value	Count	Frequency (%)
x	48602	40.0%
0	12402	10.2%
1	9998	8.2%
2	8335	6.9%
9	7533	6.2%
3	7520	6.2%
7	6263	5.2%
4	5589	4.6%
5	5305	4.4%
8	5178	4.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	72903	60.0%
Lowercase Letter	48602	40.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	12402	17.0%
1	9998	13.7%
2	8335	11.4%
9	7533	10.3%
3	7520	10.3%
7	6263	8.6%
4	5589	7.7%
5	5305	7.3%
8	5178	7.1%
6	4780	6.6%

Lowercase Letter

Value	Count	Frequency (%)
x	48602	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	72903	60.0%
Latin	48602	40.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	12402	17.0%
1	9998	13.7%
2	8335	11.4%
9	7533	10.3%
3	7520	10.3%
7	6263	8.6%
4	5589	7.7%
5	5305	7.3%
8	5178	7.1%
6	4780	6.6%

Latin

Value	Count	Frequency (%)
x	48602	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121505	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
x	48602	40.0%
0	12402	10.2%
1	9998	8.2%
2	8335	6.9%
9	7533	6.2%
3	7520	6.2%
7	6263	5.2%
4	5589	4.6%
5	5305	4.4%
8	5178	4.3%

addr_state
Categorical

Distinct	50
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

CA	4337
NY	2537
FL	1750
TX	1654
NJ	1179
Other values (45)	12844

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	48602
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	NJ
2nd row	GA
3rd row	GA
4th row	FL
5th row	CA

Common Values

Value	Count	Frequency (%)
CA	4337	17.8%
NY	2537	10.4%
FL	1750	7.2%
TX	1654	6.8%
NJ	1179	4.9%
IL	1006	4.1%
PA	951	3.9%
GA	840	3.5%
MA	827	3.4%
VA	826	3.4%
Other values (40)	8394	34.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ca	4337	17.8%
ny	2537	10.4%
fl	1750	7.2%
tx	1654	6.8%
nj	1179	4.9%
il	1006	4.1%
pa	951	3.9%
ga	840	3.5%
ma	827	3.4%
va	826	3.4%
Other values (40)	8394	34.5%

Most occurring characters

Value	Count	Frequency (%)
A	9480	19.5%
C	6101	12.6%
N	5071	10.4%
L	3281	6.8%
M	2887	5.9%
Y	2778	5.7%
T	2297	4.7%
O	2074	4.3%
I	1962	4.0%
F	1750	3.6%
Other values (14)	10921	22.5%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	48602	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	9480	19.5%
C	6101	12.6%
N	5071	10.4%
L	3281	6.8%
M	2887	5.9%
Y	2778	5.7%
T	2297	4.7%
O	2074	4.3%
I	1962	4.0%
F	1750	3.6%
Other values (14)	10921	22.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	48602	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	9480	19.5%
C	6101	12.6%
N	5071	10.4%
L	3281	6.8%
M	2887	5.9%
Y	2778	5.7%
T	2297	4.7%
O	2074	4.3%
I	1962	4.0%
F	1750	3.6%
Other values (14)	10921	22.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	48602	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	9480	19.5%
C	6101	12.6%
N	5071	10.4%
L	3281	6.8%
M	2887	5.9%
Y	2778	5.7%
T	2297	4.7%
O	2074	4.3%
I	1962	4.0%
F	1750	3.6%
Other values (14)	10921	22.5%

dti
Real number (ℝ_≥0)

Distinct	2767
Distinct (%)	11.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.29391136

Minimum	0
Maximum	29.99
Zeros	112
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	2.16
Q1	8.18
median	13.39
Q3	18.53
95-th percentile	23.78
Maximum	29.99
Range	29.99
Interquartile range (IQR)	10.35

Descriptive statistics

Standard deviation	6.646290476
Coefficient of variation (CV)	0.4999499617
Kurtosis	-0.8495096786
Mean	13.29391136
Median Absolute Deviation (MAD)	5.17
Skewness	-0.02981093437
Sum	323055.34
Variance	44.17317709
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	112	0.5%
12.48	29	0.1%
18	28	0.1%
12	27	0.1%
19.2	27	0.1%
17.04	26	0.1%
9.6	25	0.1%
8.4	22	0.1%
13.5	22	0.1%
11.5	22	0.1%
Other values (2757)	23961	98.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	112	0.5%
0.01	2	< 0.1%
0.02	3	< 0.1%
0.04	3	< 0.1%
0.05	1	< 0.1%
0.07	2	< 0.1%
0.08	2	< 0.1%
0.09	2	< 0.1%
0.12	1	< 0.1%
0.13	6	< 0.1%

Value	Count	Frequency (%)
29.99	1	< 0.1%
29.93	1	< 0.1%
29.92	1	< 0.1%
29.86	1	< 0.1%
29.85	1	< 0.1%
29.82	1	< 0.1%
29.79	1	< 0.1%
29.78	1	< 0.1%
29.76	1	< 0.1%
29.73	2	< 0.1%

delinq_2yrs
Real number (ℝ_≥0)

ZEROS

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1454261142

Minimum	0
Maximum	11
Zeros	21691
Zeros (%)	89.3%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	11
Range	11
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4948318962
Coefficient of variation (CV)	3.402634383
Kurtosis	46.15256725
Mean	0.1454261142
Median Absolute Deviation (MAD)	0
Skewness	5.308820701
Sum	3534
Variance	0.2448586055
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	21691	89.3%
1	2000	8.2%
2	411	1.7%
3	137	0.6%
4	37	0.2%
5	13	0.1%
7	4	< 0.1%
6	4	< 0.1%
8	2	< 0.1%
11	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	21691	89.3%
1	2000	8.2%
2	411	1.7%
3	137	0.6%
4	37	0.2%
5	13	0.1%
6	4	< 0.1%
7	4	< 0.1%
8	2	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
11	1	< 0.1%
9	1	< 0.1%
8	2	< 0.1%
7	4	< 0.1%
6	4	< 0.1%
5	13	0.1%
4	37	0.2%
3	137	0.6%
2	411	1.7%
1	2000	8.2%

earliest_cr_line
Categorical

HIGH CARDINALITY

Distinct	495
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

Nov-98	239
Oct-99	230
Dec-98	227
Oct-00	207
Nov-99	205
Other values (490)	23193

Length

Max length	6
Median length	6
Mean length	5.701699519
Min length	5

Characters and Unicode

Total characters	138557
Distinct characters	33
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	48 ?
Unique (%)	0.2%

Sample

1st row	1-Feb
2nd row	Feb-97
3rd row	Mar-00
4th row	4-Jun
5th row	Aug-93

Common Values

Value	Count	Frequency (%)
Nov-98	239	1.0%
Oct-99	230	0.9%
Dec-98	227	0.9%
Oct-00	207	0.9%
Nov-99	205	0.8%
Nov-97	203	0.8%
Dec-99	203	0.8%
Nov-00	201	0.8%
Sep-00	196	0.8%
Dec-97	191	0.8%
Other values (485)	22199	91.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
nov-98	239	1.0%
oct-99	230	0.9%
dec-98	227	0.9%
oct-00	207	0.9%
nov-99	205	0.8%
nov-97	203	0.8%
dec-99	203	0.8%
nov-00	201	0.8%
sep-00	196	0.8%
dec-97	191	0.8%
Other values (485)	22199	91.4%

Most occurring characters

Value	Count	Frequency (%)
-	24301	17.5%
9	14355	10.4%
e	6440	4.6%
J	5706	4.1%
u	5693	4.1%
a	5590	4.0%
8	5062	3.7%
c	4978	3.6%
0	4797	3.5%
p	3830	2.8%
Other values (23)	57805	41.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	48602	35.1%
Decimal Number	41353	29.8%
Dash Punctuation	24301	17.5%
Uppercase Letter	24301	17.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	6440	13.3%
u	5693	11.7%
a	5590	11.5%
c	4978	10.2%
p	3830	7.9%
n	3827	7.9%
r	3335	6.9%
t	2495	5.1%
v	2454	5.0%
o	2454	5.0%
Other values (4)	7506	15.4%

Decimal Number

Value	Count	Frequency (%)
9	14355	34.7%
8	5062	12.2%
0	4797	11.6%
7	2895	7.0%
4	2614	6.3%
5	2519	6.1%
6	2476	6.0%
1	2326	5.6%
3	2277	5.5%
2	2032	4.9%

Uppercase Letter

Value	Count	Frequency (%)
J	5706	23.5%
A	3699	15.2%
M	3507	14.4%
O	2495	10.3%
D	2483	10.2%
N	2454	10.1%
S	2201	9.1%
F	1756	7.2%

Dash Punctuation

Value	Count	Frequency (%)
-	24301	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	72903	52.6%
Common	65654	47.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	6440	8.8%
J	5706	7.8%
u	5693	7.8%
a	5590	7.7%
c	4978	6.8%
p	3830	5.3%
n	3827	5.2%
A	3699	5.1%
M	3507	4.8%
r	3335	4.6%
Other values (12)	26298	36.1%

Common

Value	Count	Frequency (%)
-	24301	37.0%
9	14355	21.9%
8	5062	7.7%
0	4797	7.3%
7	2895	4.4%
4	2614	4.0%
5	2519	3.8%
6	2476	3.8%
1	2326	3.5%
3	2277	3.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	138557	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	24301	17.5%
9	14355	10.4%
e	6440	4.6%
J	5706	4.1%
u	5693	4.1%
a	5590	4.0%
8	5062	3.7%
c	4978	3.6%
0	4797	3.5%
p	3830	2.8%
Other values (23)	57805	41.7%

inq_last_6mths
Real number (ℝ_≥0)

ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.8703345541

Minimum	0
Maximum	8
Zeros	11833
Zeros (%)	48.7%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	1
95-th percentile	3
Maximum	8
Range	8
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.071179193
Coefficient of variation (CV)	1.230767166
Kurtosis	2.511495036
Mean	0.8703345541
Median Absolute Deviation (MAD)	1
Skewness	1.378090416
Sum	21150
Variance	1.147424863
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	11833	48.7%
1	6634	27.3%
2	3606	14.8%
3	1869	7.7%
4	206	0.8%
5	86	0.4%
6	36	0.1%
7	21	0.1%
8	10	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11833	48.7%
1	6634	27.3%
2	3606	14.8%
3	1869	7.7%
4	206	0.8%
5	86	0.4%
6	36	0.1%
7	21	0.1%
8	10	< 0.1%

Value	Count	Frequency (%)
8	10	< 0.1%
7	21	0.1%
6	36	0.1%
5	86	0.4%
4	206	0.8%
3	1869	7.7%
2	3606	14.8%
1	6634	27.3%
0	11833	48.7%

open_acc
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	38
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.347475413

Minimum	2
Maximum	44
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	2
5-th percentile	3
Q1	6
median	9
Q3	12
95-th percentile	18
Maximum	44
Range	42
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.398961333
Coefficient of variation (CV)	0.4706042154
Kurtosis	1.744522577
Mean	9.347475413
Median Absolute Deviation (MAD)	3
Skewness	1.01349455
Sum	227153
Variance	19.35086081
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
7	2493	10.3%
8	2398	9.9%
6	2388	9.8%
9	2316	9.5%
10	1978	8.1%
5	1941	8.0%
11	1683	6.9%
12	1410	5.8%
4	1373	5.6%
13	1187	4.9%
Other values (28)	5134	21.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	345	1.4%
3	875	3.6%
4	1373	5.6%
5	1941	8.0%
6	2388	9.8%
7	2493	10.3%
8	2398	9.9%
9	2316	9.5%
10	1978	8.1%
11	1683	6.9%

Value	Count	Frequency (%)
44	1	< 0.1%
41	1	< 0.1%
39	1	< 0.1%
38	1	< 0.1%
36	1	< 0.1%
34	5	< 0.1%
33	2	< 0.1%
32	2	< 0.1%
31	5	< 0.1%
30	8	< 0.1%

pub_rec
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

0	23050
1	1212
2	33
3	4
4	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	24301
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	23050	94.9%
1	1212	5.0%
2	33	0.1%
3	4	< 0.1%
4	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	23050	94.9%
1	1212	5.0%
2	33	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	23050	94.9%
1	1212	5.0%
2	33	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	24301	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	23050	94.9%
1	1212	5.0%
2	33	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	24301	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	23050	94.9%
1	1212	5.0%
2	33	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24301	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	23050	94.9%
1	1212	5.0%
2	33	0.1%
3	4	< 0.1%
4	2	< 0.1%

revol_bal
Real number (ℝ_≥0)

ZEROS

Distinct	16118
Distinct (%)	66.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13427.54738

Minimum	0
Maximum	149588
Zeros	606
Zeros (%)	2.5%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	350
Q1	3794
median	8906
Q3	17102
95-th percentile	41844
Maximum	149588
Range	149588
Interquartile range (IQR)	13308

Descriptive statistics

Standard deviation	15801.73578
Coefficient of variation (CV)	1.176814747
Kurtosis	14.45815964
Mean	13427.54738
Median Absolute Deviation (MAD)	6014
Skewness	3.144976502
Sum	326302829
Variance	249694853.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	606	2.5%
1	9	< 0.1%
23	8	< 0.1%
39	7	< 0.1%
482	7	< 0.1%
798	7	< 0.1%
52	7	< 0.1%
452	7	< 0.1%
1821	6	< 0.1%
1575	6	< 0.1%
Other values (16108)	23631	97.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	606	2.5%
1	9	< 0.1%
2	3	< 0.1%
3	4	< 0.1%
4	3	< 0.1%
5	6	< 0.1%
6	4	< 0.1%
7	1	< 0.1%
8	3	< 0.1%
9	3	< 0.1%

Value	Count	Frequency (%)
149588	1	< 0.1%
148804	1	< 0.1%
147897	1	< 0.1%
147750	1	< 0.1%
147559	1	< 0.1%
147451	1	< 0.1%
146472	1	< 0.1%
145711	1	< 0.1%
145518	1	< 0.1%
144723	1	< 0.1%

revol_util
Categorical

HIGH CARDINALITY

Distinct	1059
Distinct (%)	4.4%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

0%	592
63%	44
66.60%	42
0.20%	42
57.70%	40
Other values (1054)	23541

Length

Max length	6
Median length	6
Mean length	5.519484795
Min length	0

Characters and Unicode

Total characters	134129
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	58 ?
Unique (%)	0.2%

Sample

1st row	1.20%
2nd row	14%
3rd row	34.40%
4th row	9.40%
5th row	2.80%

Common Values

Value	Count	Frequency (%)
0%	592	2.4%
63%	44	0.2%
66.60%	42	0.2%
0.20%	42	0.2%
57.70%	40	0.2%
46.40%	39	0.2%
70.40%	39	0.2%
68.70%	39	0.2%
48.90%	39	0.2%
57.40%	38	0.2%
Other values (1049)	23347	96.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	592	2.4%
63	44	0.2%
66.60	42	0.2%
0.20	42	0.2%
57.70	40	0.2%
46.40	39	0.2%
70.40	39	0.2%
68.70	39	0.2%
48.90	39	0.2%
57.40	38	0.2%
Other values (1048)	23318	96.1%

Most occurring characters

Value	Count	Frequency (%)
0	24288	18.1%
%	24272	18.1%
.	21327	15.9%
4	7486	5.6%
7	7380	5.5%
5	7370	5.5%
6	7342	5.5%
3	7296	5.4%
2	7035	5.2%
8	7010	5.2%
Other values (2)	13323	9.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	88530	66.0%
Other Punctuation	45599	34.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	24288	27.4%
4	7486	8.5%
7	7380	8.3%
5	7370	8.3%
6	7342	8.3%
3	7296	8.2%
2	7035	7.9%
8	7010	7.9%
9	6670	7.5%
1	6653	7.5%

Other Punctuation

Value	Count	Frequency (%)
%	24272	53.2%
.	21327	46.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	134129	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	24288	18.1%
%	24272	18.1%
.	21327	15.9%
4	7486	5.6%
7	7380	5.5%
5	7370	5.5%
6	7342	5.5%
3	7296	5.4%
2	7035	5.2%
8	7010	5.2%
Other values (2)	13323	9.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	134129	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	24288	18.1%
%	24272	18.1%
.	21327	15.9%
4	7486	5.6%
7	7380	5.5%
5	7370	5.5%
6	7342	5.5%
3	7296	5.4%
2	7035	5.2%
8	7010	5.2%
Other values (2)	13323	9.9%

total_acc
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	73
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	22.14139336

Minimum	2
Maximum	79
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	2
5-th percentile	7
Q1	14
median	20
Q3	29
95-th percentile	43
Maximum	79
Range	77
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	11.36428267
Coefficient of variation (CV)	0.5132595989
Kurtosis	0.6494638644
Mean	22.14139336
Median Absolute Deviation (MAD)	7
Skewness	0.8207349499
Sum	538058
Variance	129.1469207
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
16	922	3.8%
15	902	3.7%
17	900	3.7%
14	893	3.7%
20	879	3.6%
18	873	3.6%
13	849	3.5%
21	845	3.5%
12	816	3.4%
19	814	3.3%
Other values (63)	15608	64.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	1	< 0.1%
3	95	0.4%
4	253	1.0%
5	331	1.4%
6	413	1.7%
7	509	2.1%
8	606	2.5%
9	665	2.7%
10	696	2.9%
11	746	3.1%

Value	Count	Frequency (%)
79	2	< 0.1%
78	1	< 0.1%
75	2	< 0.1%
73	1	< 0.1%
72	1	< 0.1%
70	1	< 0.1%
69	1	< 0.1%
67	4	< 0.1%
66	4	< 0.1%
65	2	< 0.1%

total_pymnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	23403
Distinct (%)	96.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11968.51764

Minimum	0
Maximum	58480.13992
Zeros	8
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	1923.16829
Q1	5598.284713
median	9884.01
Q3	16204.15357
95-th percentile	29675.9581
Maximum	58480.13992
Range	58480.13992
Interquartile range (IQR)	10605.86886

Descriptive statistics

Standard deviation	8770.861953
Coefficient of variation (CV)	0.7328277583
Kurtosis	2.098113535
Mean	11968.51764
Median Absolute Deviation (MAD)	4877.779336
Skewness	1.348177624
Sum	290846947.2
Variance	76928019.39
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11196.56943	19	0.1%
13435.90021	10	< 0.1%
13263.95464	10	< 0.1%
5478.387981	9	< 0.1%
13148.13786	9	< 0.1%
10956.77596	9	< 0.1%
0	8	< 0.1%
5557.025543	8	< 0.1%
11163.54473	7	< 0.1%
14346.47905	7	< 0.1%
Other values (23393)	24205	99.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8	< 0.1%
33.73	1	< 0.1%
44.92	1	< 0.1%
44.96	1	< 0.1%
66.77	1	< 0.1%
67.32	1	< 0.1%
69.64	1	< 0.1%
69.77	1	< 0.1%
76.33	1	< 0.1%
78.93	1	< 0.1%

Value	Count	Frequency (%)
58480.13992	1	< 0.1%
56849.26986	1	< 0.1%
56199.43995	1	< 0.1%
55906.9499	1	< 0.1%
55768.77995	1	< 0.1%
54774.41992	1	< 0.1%
54714.7599	1	< 0.1%
54132.39808	1	< 0.1%
54111.73995	1	< 0.1%
54005.47996	1	< 0.1%

total_pymnt_inv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	23267
Distinct (%)	95.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11367.89998

Minimum	0
Maximum	58438.37
Zeros	109
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	1460.13
Q1	5149.52
median	9263.59
Q3	15439.11
95-th percentile	28971.85
Maximum	58438.37
Range	58438.37
Interquartile range (IQR)	10289.59

Descriptive statistics

Standard deviation	8652.249737
Coefficient of variation (CV)	0.7611124091
Kurtosis	2.148563125
Mean	11367.89998
Median Absolute Deviation (MAD)	4799.98
Skewness	1.362242987
Sum	276251337.3
Variance	74861425.51
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	109	0.4%
6717.95	11	< 0.1%
6514.52	10	< 0.1%
11196.57	10	< 0.1%
7173.24	8	< 0.1%
10956.78	8	< 0.1%
13148.14	8	< 0.1%
5478.39	8	< 0.1%
13263.95	7	< 0.1%
2171.51	7	< 0.1%
Other values (23257)	24115	99.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	109	0.4%
12.65	1	< 0.1%
21.6	1	< 0.1%
25.18	1	< 0.1%
26.19	1	< 0.1%
33.73	1	< 0.1%
40.04	1	< 0.1%
44.92	1	< 0.1%
44.96	1	< 0.1%
53.95	1	< 0.1%

Value	Count	Frequency (%)
58438.37	1	< 0.1%
56515.16	1	< 0.1%
55867.02	1	< 0.1%
55579.28	1	< 0.1%
54675.68	1	< 0.1%
53954.4	1	< 0.1%
53928.33	1	< 0.1%
53118.31	1	< 0.1%
53018.62	1	< 0.1%
52847.96	1	< 0.1%

total_rec_prncp
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4543
Distinct (%)	18.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9723.016746

Minimum	0
Maximum	35000.01
Zeros	48
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	1363.97
Q1	4700
median	8000
Q3	13250
95-th percentile	24250
Maximum	35000.01
Range	35000.01
Interquartile range (IQR)	8550

Descriptive statistics

Standard deviation	6971.62505
Coefficient of variation (CV)	0.7170228368
Kurtosis	1.215660751
Mean	9723.016746
Median Absolute Deviation (MAD)	4000
Skewness	1.139092078
Sum	236279030
Variance	48603555.84
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	1461	6.0%
12000	1177	4.8%
6000	1057	4.3%
5000	1051	4.3%
15000	878	3.6%
8000	798	3.3%
20000	672	2.8%
4000	582	2.4%
3000	553	2.3%
7000	538	2.2%
Other values (4533)	15534	63.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	48	0.2%
21.93	1	< 0.1%
22.5	1	< 0.1%
24.87	1	< 0.1%
30.32	1	< 0.1%
34.5	1	< 0.1%
35.14	1	< 0.1%
35.8	1	< 0.1%
38.23	1	< 0.1%
40.23	1	< 0.1%

Value	Count	Frequency (%)
35000.01	1	< 0.1%
35000	222	0.9%
34999.99	1	< 0.1%
34999.97	1	< 0.1%
34800	1	< 0.1%
34525	1	< 0.1%
34475.01	1	< 0.1%
34475	2	< 0.1%
34250	1	< 0.1%
34000	8	< 0.1%

total_rec_int
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	22197
Distinct (%)	91.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2143.968805

Minimum	0
Maximum	23480.14
Zeros	45
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	186.74
Q1	664.42
median	1336.55
Q3	2711.22
95-th percentile	6888.21
Maximum	23480.14
Range	23480.14
Interquartile range (IQR)	2046.8

Descriptive statistics

Standard deviation	2388.945182
Coefficient of variation (CV)	1.114263032
Kurtosis	9.956250843
Mean	2143.968805
Median Absolute Deviation (MAD)	838.1
Skewness	2.671187185
Sum	52100585.94
Variance	5707059.085
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	45	0.2%
1196.57	19	0.1%
717.95	13	0.1%
1148.14	11	< 0.1%
514.52	10	< 0.1%
1435.9	10	< 0.1%
1263.95	10	< 0.1%
1500.79	10	< 0.1%
956.78	10	< 0.1%
478.39	9	< 0.1%
Other values (22187)	24154	99.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	45	0.2%
6.22	1	< 0.1%
6.27	1	< 0.1%
7.2	2	< 0.1%
8.23	1	< 0.1%
9.58	1	< 0.1%
10.26	1	< 0.1%
11.17	1	< 0.1%
11.18	1	< 0.1%
11.23	1	< 0.1%

Value	Count	Frequency (%)
23480.14	1	< 0.1%
22122.3	1	< 0.1%
21849.27	1	< 0.1%
21199.44	1	< 0.1%
20909.99	1	< 0.1%
20906.95	1	< 0.1%
20768.78	1	< 0.1%
19820.91	1	< 0.1%
19774.42	1	< 0.1%
19714.76	1	< 0.1%

total_rec_late_fee
Real number (ℝ_≥0)

ZEROS

Distinct	841
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.35800838

Minimum	0
Maximum	166.4297107
Zeros	23074
Zeros (%)	95.0%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	4.41
Maximum	166.4297107
Range	166.4297107
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	7.397470223
Coefficient of variation (CV)	5.447293502
Kurtosis	100.8881406
Mean	1.35800838
Median Absolute Deviation (MAD)	0
Skewness	8.525174382
Sum	33000.96164
Variance	54.7225657
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	23074	95.0%
15	136	0.6%
15.00000001	36	0.1%
15.00000002	32	0.1%
30	29	0.1%
14.99999999	24	0.1%
15.00000003	21	0.1%
14.99999997	20	0.1%
14.99999998	17	0.1%
15.00000004	16	0.1%
Other values (831)	896	3.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	23074	95.0%
0.01	1	< 0.1%
0.060799751	1	< 0.1%
0.101704562	1	< 0.1%
0.139999999	1	< 0.1%
0.180082904	1	< 0.1%
0.18477362	1	< 0.1%
0.27	1	< 0.1%
0.302036553	1	< 0.1%
1	1	< 0.1%

Value	Count	Frequency (%)
166.4297107	1	< 0.1%
165.69	1	< 0.1%
146.6000003	1	< 0.1%
146.04	1	< 0.1%
130.5970372	1	< 0.1%
127.7878136	1	< 0.1%
120.81	1	< 0.1%
119.9999998	1	< 0.1%
119.07	1	< 0.1%
116.1000001	1	< 0.1%

recoveries
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2551
Distinct (%)	10.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	100.1741605

Minimum	0
Maximum	29623.35
Zeros	21677
Zeros (%)	89.2%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	389.54
Maximum	29623.35
Range	29623.35
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	719.3517881
Coefficient of variation (CV)	7.181011395
Kurtosis	378.0336495
Mean	100.1741605
Median Absolute Deviation (MAD)	0
Skewness	16.41503055
Sum	2434332.274
Variance	517466.995
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	21677	89.2%
10.07	3	< 0.1%
13.59	3	< 0.1%
24.06	2	< 0.1%
138.02	2	< 0.1%
220.23	2	< 0.1%
9.67	2	< 0.1%
9.77	2	< 0.1%
20.2	2	< 0.1%
139.62	2	< 0.1%
Other values (2541)	2604	10.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	21677	89.2%
6.3	1	< 0.1%
8.19	1	< 0.1%
8.36	1	< 0.1%
8.46	1	< 0.1%
8.56	1	< 0.1%
8.88	1	< 0.1%
8.89	1	< 0.1%
9.09	1	< 0.1%
9.11	1	< 0.1%

Value	Count	Frequency (%)
29623.35	1	< 0.1%
22943.37	1	< 0.1%
21810.31	1	< 0.1%
19508.26	1	< 0.1%
16268.35	1	< 0.1%
16066.02	1	< 0.1%
16008.02	1	< 0.1%
15914.93	1	< 0.1%
15236.31	1	< 0.1%
14906.81	1	< 0.1%

collection_recovery_fee
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	1800
Distinct (%)	7.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12.35402273

Minimum	0
Maximum	5602.72
Zeros	21936
Zeros (%)	90.3%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	5.49
Maximum	5602.72
Range	5602.72
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	139.801427
Coefficient of variation (CV)	11.31626759
Kurtosis	671.2703989
Mean	12.35402273
Median Absolute Deviation (MAD)	0
Skewness	22.72682334
Sum	300215.1063
Variance	19544.43899
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	21936	90.3%
1.6	7	< 0.1%
0.8	7	< 0.1%
1.8	7	< 0.1%
2.02	6	< 0.1%
4.95	6	< 0.1%
3.71	6	< 0.1%
3.39	6	< 0.1%
4.73	5	< 0.1%
2.55	5	< 0.1%
Other values (1790)	2310	9.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	21936	90.3%
0.063	1	< 0.1%
0.134799995	1	< 0.1%
0.1393	1	< 0.1%
0.1952	1	< 0.1%
0.200700001	1	< 0.1%
0.23	1	< 0.1%
0.2462	1	< 0.1%
0.251699999	1	< 0.1%
0.2543	1	< 0.1%

Value	Count	Frequency (%)
5602.72	1	< 0.1%
5569.92	1	< 0.1%
5216.74	1	< 0.1%
4902.08	1	< 0.1%
4900.75	1	< 0.1%
4821.78	1	< 0.1%
4254.91	1	< 0.1%
3988.81	1	< 0.1%
3926.15	1	< 0.1%
3590.6795	1	< 0.1%

last_pymnt_d
Categorical

HIGH CARDINALITY

Distinct	102
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

13-Mar	628
13-May	586
14-Dec	553
13-Feb	548
12-Aug	543
Other values (97)	21443

Length

Max length	6
Median length	6
Mean length	5.971523806
Min length	0

Characters and Unicode

Total characters	145114
Distinct characters	32
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	< 0.1%

Sample

1st row	11-Mar
2nd row	10-Mar
3rd row	11-Dec
4th row	15-Sep
5th row	10-May

Common Values

Value	Count	Frequency (%)
13-Mar	628	2.6%
13-May	586	2.4%
14-Dec	553	2.3%
13-Feb	548	2.3%
12-Aug	543	2.2%
14-Jan	543	2.2%
14-Jul	534	2.2%
12-Mar	531	2.2%
14-Mar	529	2.2%
14-Aug	523	2.2%
Other values (92)	18783	77.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
13-mar	628	2.6%
13-may	586	2.4%
14-dec	553	2.3%
13-feb	548	2.3%
12-aug	543	2.2%
14-jan	543	2.2%
14-jul	534	2.2%
12-mar	531	2.2%
14-mar	529	2.2%
14-oct	523	2.2%
Other values (91)	18738	77.3%

Most occurring characters

Value	Count	Frequency (%)
1	26987	18.6%
-	24256	16.7%
a	6318	4.4%
e	6109	4.2%
u	5983	4.1%
3	5940	4.1%
4	5836	4.0%
J	5797	4.0%
2	5607	3.9%
M	4401	3.0%
Other values (22)	47880	33.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	48512	33.4%
Decimal Number	48090	33.1%
Dash Punctuation	24256	16.7%
Uppercase Letter	24256	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	6318	13.0%
e	6109	12.6%
u	5983	12.3%
r	4343	9.0%
c	4241	8.7%
p	3907	8.1%
n	3763	7.8%
g	2103	4.3%
t	2039	4.2%
l	2034	4.2%
Other values (4)	7672	15.8%

Decimal Number

Value	Count	Frequency (%)
1	26987	56.1%
3	5940	12.4%
4	5836	12.1%
2	5607	11.7%
5	1586	3.3%
0	1137	2.4%
6	575	1.2%
9	337	0.7%
8	85	0.2%

Uppercase Letter

Value	Count	Frequency (%)
J	5797	23.9%
M	4401	18.1%
A	4069	16.8%
D	2202	9.1%
O	2039	8.4%
F	1966	8.1%
S	1941	8.0%
N	1841	7.6%

Dash Punctuation

Value	Count	Frequency (%)
-	24256	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	72768	50.1%
Common	72346	49.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	6318	8.7%
e	6109	8.4%
u	5983	8.2%
J	5797	8.0%
M	4401	6.0%
r	4343	6.0%
c	4241	5.8%
A	4069	5.6%
p	3907	5.4%
n	3763	5.2%
Other values (12)	23837	32.8%

Common

Value	Count	Frequency (%)
1	26987	37.3%
-	24256	33.5%
3	5940	8.2%
4	5836	8.1%
2	5607	7.8%
5	1586	2.2%
0	1137	1.6%
6	575	0.8%
9	337	0.5%
8	85	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	145114	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	26987	18.6%
-	24256	16.7%
a	6318	4.4%
e	6109	4.2%
u	5983	4.1%
3	5940	4.1%
4	5836	4.0%
J	5797	4.0%
2	5607	3.9%
M	4401	3.0%
Other values (22)	47880	33.0%

last_pymnt_amnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	22582
Distinct (%)	92.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2771.94458

Minimum	0
Maximum	36115.2
Zeros	45
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	190.0 KiB

Quantile statistics

Minimum	0
5-th percentile	43.24
Q1	223.36
median	586.18
Q3	3514.26
95-th percentile	12418.61
Maximum	36115.2
Range	36115.2
Interquartile range (IQR)	3290.9

Descriptive statistics

Standard deviation	4505.872171
Coefficient of variation (CV)	1.62552751
Kurtosis	8.524347287
Mean	2771.94458
Median Absolute Deviation (MAD)	497.19
Skewness	2.654086317
Sum	67361025.25
Variance	20302884.02
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	45	0.2%
200	11	< 0.1%
400	10	< 0.1%
50	9	< 0.1%
100	9	< 0.1%
500	8	< 0.1%
150	8	< 0.1%
324.42	7	< 0.1%
250	6	< 0.1%
276.06	6	< 0.1%
Other values (22572)	24182	99.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	45	0.2%
0.01	1	< 0.1%
0.16	1	< 0.1%
0.24	1	< 0.1%
0.25	1	< 0.1%
0.28	1	< 0.1%
0.35	1	< 0.1%
0.36	2	< 0.1%
0.44	3	< 0.1%
0.51	1	< 0.1%

Value	Count	Frequency (%)
36115.2	1	< 0.1%
35596.41	1	< 0.1%
35479.89	1	< 0.1%
35337.09	1	< 0.1%
35322.96	1	< 0.1%
35283.09	1	< 0.1%
35139.61	1	< 0.1%
34981.66	1	< 0.1%
34852.54	1	< 0.1%
34675.92	1	< 0.1%

last_credit_pull_d
Categorical

HIGH CARDINALITY

Distinct	102
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

16-May	5932
16-Apr	1526
16-Mar	723
13-Feb	504
16-Feb	453
Other values (97)	15163

Length

Max length	6
Median length	6
Mean length	5.992839801
Min length	5

Characters and Unicode

Total characters	145632
Distinct characters	33
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	11-Jul
2nd row	10-Feb
3rd row	11-Dec
4th row	16-May
5th row	10-May

Common Values

Value	Count	Frequency (%)
16-May	5932	24.4%
16-Apr	1526	6.3%
16-Mar	723	3.0%
13-Feb	504	2.1%
16-Feb	453	1.9%
15-Dec	418	1.7%
16-Jan	412	1.7%
15-Sep	361	1.5%
13-Mar	352	1.4%
14-Mar	351	1.4%
Other values (92)	13269	54.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
16-may	5932	24.4%
16-apr	1526	6.3%
16-mar	723	3.0%
13-feb	504	2.1%
16-feb	453	1.9%
15-dec	418	1.7%
16-jan	412	1.7%
15-sep	361	1.5%
13-mar	352	1.4%
14-mar	351	1.4%
Other values (92)	13269	54.6%

Most occurring characters

Value	Count	Frequency (%)
1	25511	17.5%
-	24301	16.7%
a	10509	7.2%
M	9208	6.3%
6	9046	6.2%
y	7144	4.9%
e	4748	3.3%
r	4729	3.2%
p	4018	2.8%
A	3975	2.7%
Other values (23)	42443	29.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	48602	33.4%
Decimal Number	48428	33.3%
Dash Punctuation	24301	16.7%
Uppercase Letter	24301	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	10509	21.6%
y	7144	14.7%
e	4748	9.8%
r	4729	9.7%
p	4018	8.3%
u	3659	7.5%
c	2790	5.7%
n	2374	4.9%
b	1908	3.9%
o	1417	2.9%
Other values (4)	5306	10.9%

Decimal Number

Value	Count	Frequency (%)
1	25511	52.7%
6	9046	18.7%
4	3862	8.0%
5	3593	7.4%
3	3205	6.6%
2	2514	5.2%
0	523	1.1%
9	136	0.3%
8	29	0.1%
7	9	< 0.1%

Uppercase Letter

Value	Count	Frequency (%)
M	9208	37.9%
A	3975	16.4%
J	3650	15.0%
F	1908	7.9%
D	1487	6.1%
N	1417	5.8%
S	1353	5.6%
O	1303	5.4%

Dash Punctuation

Value	Count	Frequency (%)
-	24301	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	72903	50.1%
Common	72729	49.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	10509	14.4%
M	9208	12.6%
y	7144	9.8%
e	4748	6.5%
r	4729	6.5%
p	4018	5.5%
A	3975	5.5%
u	3659	5.0%
J	3650	5.0%
c	2790	3.8%
Other values (12)	18473	25.3%

Common

Value	Count	Frequency (%)
1	25511	35.1%
-	24301	33.4%
6	9046	12.4%
4	3862	5.3%
5	3593	4.9%
3	3205	4.4%
2	2514	3.5%
0	523	0.7%
9	136	0.2%
8	29	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	145632	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	25511	17.5%
-	24301	16.7%
a	10509	7.2%
M	9208	6.3%
6	9046	6.2%
y	7144	4.9%
e	4748	3.3%
r	4729	3.2%
p	4018	2.8%
A	3975	2.7%
Other values (23)	42443	29.1%

pub_rec_bankruptcies
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	190.0 KiB

0.0	23303
1.0	994
2.0	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	72903
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	23303	95.9%
1.0	994	4.1%
2.0	4	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	23303	95.9%
1.0	994	4.1%
2.0	4	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	47604	65.3%
.	24301	33.3%
1	994	1.4%
2	4	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	48602	66.7%
Other Punctuation	24301	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	47604	97.9%
1	994	2.0%
2	4	< 0.1%

Other Punctuation

Value	Count	Frequency (%)
.	24301	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	72903	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	47604	65.3%
.	24301	33.3%
1	994	1.4%
2	4	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	72903	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	47604	65.3%
.	24301	33.3%
1	994	1.4%
2	4	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	df_index	loan_amnt	funded_amnt	funded_amnt_inv	term	int_rate	installment	grade	sub_grade	emp_title	emp_length	home_ownership	annual_inc	verification_status	issue_d	loan_status	desc	purpose	title	zip_code	addr_state	dti	delinq_2yrs	earliest_cr_line	inq_last_6mths	open_acc	pub_rec	revol_bal	revol_util	total_acc	total_pymnt	total_pymnt_inv	total_rec_prncp	total_rec_int	recoveries	collection_recovery_fee	last_pymnt_d	last_pymnt_amnt	last_credit_pull_d
0	0	10000	10000	9950.000000	36	7.51%	311.11	A	A4	15	10	RENT	30000.0	Source Verified	10-Sep	0	Borrower added on 08/30/10 > thank you<br/>	home_improvement	homeimproement	076xx	NJ	5.00	0	1-Feb	3	19	0	1450	1.20%	48	2247.210000	2235.98	1509.91	350.87	386.43	3.96	11-Mar	311.11	11-Jul
1	1	15000	15000	14800.000000	36	8.94%	476.58	A	A5	1400	1	RENT	147000.0	Not Verified	10-Jan	1	Borrower added on 01/14/10 > Green city housing project<br/> Borrower added on 01/23/10 > I mistyped in the application. $1400 is the current rent we pay. <br/><br/>My employer is Emerson, and my role is marketing and biz dev director. Been with them for 3 years now. My 2009 annual compensation was ~160K. <br/><br/>I have zero credit card debt or car loans. Purpose of the loan is to buy real estate in my home town in India. It costs ~$140K. Rather than taking a mortgage there, I want to buy the property outright. I used $125K from my savings, and I am short $15K. The name of the building community is Green City - www.vplprojects.com.<br/>	other	Green City	300xx	GA	3.47	0	Feb-97	0	6	0	4910	14%	17	15112.760000	14911.26	15000.00	112.76	0.00	0.00	10-Mar	15114.03	10-Feb
2	2	2000	2000	2000.000000	36	13.57%	67.94	C	C3	36000	4	OWN	36000.0	Not Verified	9-Oct	1		major_purchase	payoff w/in 2 years	310xx	GA	7.83	0	Mar-00	0	8	0	1790	34.40%	10	2354.966827	2354.97	2000.00	354.97	0.00	0.00	11-Dec	101.78	11-Dec
3	4	14000	14000	14000.000000	60	17.49%	351.64	D	D5	old palm inc	5	MORTGAGE	50000.0	Not Verified	11-Jul	1	Borrower added on 06/29/11 > thanks for the help.<br/>	debt_consolidation	save %	334xx	FL	21.24	1	4-Jun	1	9	1	553	9.40%	27	20804.230020	20804.23	14000.00	6804.23	0.00	0.00	15-Sep	3943.27	16-May
4	5	12000	12000	11900.000000	36	8.94%	381.26	A	A5	Brocade Communications	7	MORTGAGE	294000.0	Not Verified	9-Dec	1		other	Invest in Lending Club Notes	939xx	CA	0.50	0	Aug-93	0	11	0	5306	2.80%	21	12344.811770	12241.94	12000.00	344.81	0.00	0.00	10-May	11204.30	10-May
5	6	10000	6525	6480.473624	60	7.88%	131.93	A	A5	CenturyLink	4	MORTGAGE	65000.0	Not Verified	10-Jun	1	Borrower added on 05/25/10 > I obtained a discover personal loan 2mths ago at a fixed rate of appx 18% for 72 mths to consolidate all revolving debt except 1 low rate card. This loan is to reduce both the term and rate of that loan in order to be debt free w/in 5 years. The only credit card balance I have is a 2nd Discover card which is a fixed balance transfer rate of 2.99% until 2013 which is being paid at a rate to accomplish $0 balance by 01/2013. Original debt was generated from costs to prepare home to sell which didn't sell. No other debt exists except fixed mortgage - not even a car payment.<br/>	credit_card	Discover	640xx	MO	7.62	1	Feb-96	1	13	0	5629	19.10%	23	7908.889997	7846.07	6525.00	1383.89	0.00	0.00	15-Feb	668.53	15-Sep
6	7	7800	7800	7800.000000	60	14.91%	185.20	D	D2	Department of Homeland Security	4	MORTGAGE	94000.0	Verified	11-Feb	1	Borrower added on 01/30/11 > Money will be used to make a lump some alimony payment.<br/> Borrower added on 01/30/11 > Lump sum alimony payment.<br/> Borrower added on 01/30/11 > Average monthly breakdown:<br/><br/>Mortgage: 1206<br/><br/>Total credit card payments: 1358<br/><br/>Car/Insurance: 300<br/><br/>Miscellaneous expenses: 300<br/>	other	Help With Divorce Expenses	480xx	MI	12.96	0	Feb-00	1	11	0	2317	37.40%	37	9864.289537	9864.29	7800.00	2064.29	0.00	0.00	13-May	58.59	16-May
7	8	18825	18825	18825.000000	36	7.90%	589.04	A	A4	Down To Earth Distributors, Inc.	5	RENT	42000.0	Not Verified	11-Oct	1	Borrower added on 10/03/11 > Loan to consolidate debt of a credit card and two student loans into one monthly payment. Thanks for considering investing in our financial health!<br/>	debt_consolidation	Consolidation Loan	974xx	OR	22.74	0	Aug-98	0	7	0	22121	55.40%	22	20958.528940	20958.53	18825.00	2133.53	0.00	0.00	13-Dec	239.16	13-Dec
8	10	2600	2600	2600.000000	36	12.53%	87.02	B	B5	Plaid, Inc.	2	RENT	40792.0	Not Verified	9-Oct	1	560296 added on 10/20/09 > I am a graphic designer and music producer in desperate need of a new computer for my career. I currently have an iMac that is several years old and has become almost unusable. I plan on using the money to buy one of the awesome new iMacs that came out today! This is my second LendingClub loan, I am a great borrower with no late payments!	major_purchase	New iMac for Work	068xx	CT	13.54	0	3-Nov	1	12	0	9847	24.10%	14	3132.393851	3132.39	2600.00	532.39	0.00	0.00	12-Nov	94.26	16-May
9	11	20000	20000	19725.000000	60	13.61%	461.34	C	C2	U.S. Dept. Of Homeland Security	8	MORTGAGE	100000.0	Verified	10-Jul	1		debt_consolidation	paydown loan	077xx	NJ	12.98	0	Jan-98	1	15	0	20984	27.50%	20	27679.645760	27299.05	20000.00	7679.65	0.00	0.00	15-Jul	513.18	16-Apr

Last rows

	df_index	loan_amnt	funded_amnt	funded_amnt_inv	term	int_rate	installment	grade	sub_grade	emp_title	emp_length	home_ownership	annual_inc	verification_status	issue_d	loan_status	desc	purpose	title	zip_code	addr_state	dti	earliest_cr_line	inq_last_6mths	open_acc	pub_rec	revol_bal	revol_util	total_acc	total_pymnt	total_pymnt_inv	total_rec_prncp	total_rec_int	last_pymnt_d	last_pymnt_amnt	last_credit_pull_d	pub_rec_bankruptcies
24291	24989	5000	5000	4900.00000	36	11.48%	164.85	B	B2	PPC Construction, Inc.	8	RENT	48000.0	Not Verified	10-Jan	1	Borrower added on 01/12/10 > I plan to pay off all existing credit card debts and I have not missed a payment and always make them on time.<br/>	debt_consolidation	operation debt free	900xx	CA	14.57	3-Mar	0	16	0	7479	42.70%	20	5934.555487	5815.86	5000.0	934.56	13-Feb	178.60	14-Feb	0.0
24292	24990	13250	13250	12950.00000	36	10.99%	433.73	B	B3	PPC Mechanical Seals	2	MORTGAGE	30000.0	Source Verified	11-Jun	1		debt_consolidation	Debt Consolidation	708xx	LA	5.88	5-Sep	0	6	0	8328	50.80%	10	15556.789530	15204.56	13250.0	2306.79	14-Jan	2590.86	16-May	0.0
24293	24991	13000	13000	12950.00000	36	5.42%	392.08	A	A1	PPD	5	MORTGAGE	59000.0	Not Verified	11-Aug	1	Borrower added on 08/18/11 > I want to consolidate and pay off 3 credit cards that mainly grew quickly due to unforeseen major car issues and veterinarian bills. I'm a good borrower as I always make my monthly payments and have a steady job as an enterprise mobile app systems developer.<br/>	debt_consolidation	Credit Card Payoff	284xx	NC	5.82	Sep-93	0	6	0	13331	62.60%	12	14114.794700	14060.51	13000.0	1114.79	14-Sep	401.72	15-Dec	0.0
24294	24992	8500	8500	8500.00000	60	10.74%	183.72	B	B4	PPD	3	MORTGAGE	38000.0	Source Verified	11-Feb	1		debt_consolidation	Credit Card Consolidation	284xx	NC	7.45	Jul-93	1	5	0	8938	51.10%	28	9990.175726	9990.18	8500.0	1490.18	13-Jan	5950.77	16-Apr	0.0
24295	24993	14575	14575	5700.00000	60	13.99%	339.06	C	C3	PPD, Inc.	10	RENT	45000.0	Not Verified	11-Jul	1	Borrower added on 07/21/11 > I plan on using the funds to pay off high interest credit cards and to have one payment a month. I am a good risk based on my credit score and that I have always been current on my debt obligations. As you can see I have been with the same company for 11 years and the company is very stable and growing.<br/> Borrower added on 07/22/11 > In addition, the monthly payment on this loan is less that what I currently have been paying monthly for all my credit cards. I plan on paying the required amount every month for the loan but will often pay more than that especially when I get items such as tax returns. bonuses and employee stock sales.<br/>	debt_consolidation	Personal Loan	284xx	NC	24.96	Aug-94	1	19	0	17670	29.20%	40	16478.712190	6444.50	14575.0	1903.71	12-Aug	12752.57	16-Mar	0.0
24296	24994	5500	5500	5500.00000	36	14.96%	190.55	D	D2	PPDG	7	MORTGAGE	52000.0	Not Verified	9-Oct	1	554340 added on 10/10/09 > TRY TO PAY OFF ALL MY DEBT ASAP.I AM GETTING THERE SO THANKS FOR ALL YOUR SUPPORT ....LUMI	debt_consolidation	FREEDOM	320xx	FL	18.74	Aug-98	2	11	0	10655	58.20%	37	6825.066783	6825.07	5500.0	1325.07	12-May	1122.20	12-Jun	0.0
24297	24995	11450	11450	11450.00000	36	8.49%	361.40	A	A5	PPG Industries	7	RENT	40000.0	Source Verified	11-Jun	1	Borrower added on 06/18/11 > I've been at my job for 7 years now. I want to pay off my high interest credit cards.<br/> Borrower added on 06/21/11 > I've never been late on payments.<br/> Borrower added on 06/27/11 > I want to pay of my credit card debt fast so that I can start planning on saving for a house.<br/>	debt_consolidation	Credit Card Consolidation	980xx	WA	21.21	4-Jan	0	10	0	10192	34%	15	13010.206030	13010.21	11450.0	1560.21	14-Jul	382.90	16-May	0.0
24298	24996	24000	24000	21100.31424	60	20.53%	642.96	G	G2	PPG Industries	10	MORTGAGE	74454.0	Verified	10-Aug	1	Borrower added on 08/21/10 > Consolidating all revolving debt to fixed debt and improve my great credit score to A1 status.<br/>	debt_consolidation	C3myboy	301xx	GA	19.95	Jun-98	3	9	0	29108	77.20%	24	33765.068310	26978.96	24000.0	9765.07	13-Jan	16500.39	16-May	0.0
24299	24997	14000	14000	11411.12089	36	17.58%	503.19	F	F2	PPG Industries	10	MORTGAGE	86000.0	Verified	9-May	1	I'm looking to consolidate high intrest loans and improve cash flow.	debt_consolidation	consolidation loan 001	440xx	OH	21.93	Jul-99	0	13	1	18991	95%	26	17917.012900	14191.06	14000.0	3917.01	11-Oct	3857.88	15-Jun	1.0
24300	24998	13400	13400	13400.00000	36	13.06%	451.89	C	C2	PPG Industries, INC	1	RENT	62040.0	Not Verified	11-Jan	1	Borrower added on 01/26/11 > I plan to use these funds to consolidate my credit cards that I used to pay off my relocation to my new job and buy furniture for the apartment. When I get this loan I will pay a lower interest than the amount I'm currently paying on my credit cards and will have a stable payment. Even when I was a student I've never missed a payment and because I'm building credit to later on buy a house I don't plan on doing it either. PPG industries, INC is a very stable company in which many of my co-workers have been working here over 30 or 40 years. The reason is that although there not the highest payers they are over the average and like I said there very stable. I work as a Mechanical Engineer developing projects. My income every month is $5,170 that subtracting taxes, health plan, 401k, saving account and all other deductions I get net of $3,900. I pay $950 monthly rent for my apartment and an average of $100 in utilities. Most of the payments that I'm making are for the credit cards, Mint.com suggested me to consolidate with you guys to save money and if all goes well I will.<br/>	debt_consolidation	Refinance Debt Loan	706xx	LA	18.84	Sep-00	3	12	0	5389	41.80%	14	16268.440550	16268.44	13400.0	2868.44	14-Feb	475.29	14-Feb	0.0

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